Analysis of GLDS-120 from NASA GeneLab
This R markdown file was auto-generated by the iDEP website Using iDEP 0.91, originally by Steven Xijin.Ge@sdstate.edu
Ge SX, Son EW, Yao R: iDEP: an integrated web application for differential expression and pathway analysis of RNA-Seq data. BMC Bioinformatics 2018, 19(1):534. PMID:30567491
First we set up the working directory to where the files are saved.
setwd('~/Documents/HTML_R/GLDS120')
R packages and iDEP core Functions. Users can also download the iDEP_core_functions.R file. Many R packages needs to be installed first. This may take hours. Each of these packages took years to develop.So be a patient thief. Sometimes dependencies needs to be installed manually. If you are using an older version of R, and having trouble with package installation, try un-install the current version of R, delete all folders and files (C:/Program Files/R/R-3.4.3), and reinstall from scratch.
if(file.exists('iDEP_core_functions.R'))
source('iDEP_core_functions.R') else
source('https://raw.githubusercontent.com/iDEP-SDSU/idep/master/shinyapps/idep/iDEP_core_functions.R')
We are using the downloaded gene expression file where gene IDs has been converted to Ensembl gene IDs. This is because the ID conversion database is too large to download. You can use your original file if your file uses Ensembl ID, or you do not want to use the pathway files available in iDEP (or it is not available).
inputFile <- 'GLDS120_Expression.csv'
sampleInfoFile <- 'GLDS120_Sampleinfo.csv'
gldsMetadataFile <- 'GLDS120_Metadata.csv'
geneInfoFile <- 'Arabidopsis_thaliana__athaliana_eg_gene_GeneInfo.csv' #Gene symbols, location etc.
geneSetFile <- 'Arabidopsis_thaliana__athaliana_eg_gene.db' # pathway database in SQL; can be GMT format
STRING10_speciesFile <- 'https://raw.githubusercontent.com/iDEP-SDSU/idep/master/shinyapps/idep/STRING10_species.csv'
Parameters for reading data
input_missingValue <- 'geneMedian' #Missing values imputation method
input_dataFileFormat <- 1 #1- read counts, 2 FKPM/RPKM or DNA microarray
input_minCounts <- 0.5 #Min counts
input_NminSamples <- 1 #Minimum number of samples
input_countsLogStart <- 4 #Pseudo count for log CPM
input_CountsTransform <- 1 #Methods for data transformation of counts. 1-EdgeR's logCPM 2-VST, 3-rlog
readMetadata.out <- readMetadata(gldsMetadataFile)
library(knitr) # install if needed. for showing tables with kable
library(kableExtra)
kable( readMetadata.out ) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%")
| Col0_GC_Alight_Rep1 | Col0_GC_Alight_Rep2 | Col0_GC_Alight_Rep3 | Col0_GC_dark_Rep1 | Col0_GC_dark_Rep2 | Col0_GC_dark_Rep3 | Ws_GC_Alight_Rep1 | Ws_GC_Alight_Rep2 | Ws_GC_Alight_Rep3 | Ws_GC_dark_Rep1 | Ws_GC_dark_Rep2 | Ws_GC_dark_Rep3 | Col0PhyD_GC_Alight_Rep1 | Col0PhyD_GC_Alight_Rep2 | Col0PhyD_GC_Alight_Rep3 | Col0PhyD_GC_dark_Rep1 | Col0PhyD_GC_dark_Rep2 | Col0PhyD_GC_dark_Rep3 | Col0_FLT_Alight_Rep1 | Col0_FLT_Alight_Rep2 | Col0_FLT_Alight_Rep3 | Col0_FLT_dark_Rep1 | Col0_FLT_dark_Rep2 | Col0_FLT_dark_Rep3 | Ws_FLT_Alight_Rep1 | Ws_FLT_Alight_Rep2 | Ws_FLT_Alight_Rep3 | Ws_FLT_dark_Rep1 | Ws_FLT_dark_Rep2 | Ws_FLT_dark_Rep3 | Col0PhyD_FLT_Alight_Rep1 | Col0PhyD_FLT_Alight_Rep2 | Col0PhyD_FLT_Alight_Rep3 | Col0PhyD_FLT_dark_Rep1 | Col0PhyD_FLT_dark_Rep2 | Col0PhyD_FLT_dark_Rep3 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Sample.LongId | Atha.Col.0.root.GC.Alight.Rep1.GSM2493759.RNAseq.RNAseq | Atha.Col.0.root.GC.Alight.Rep2.GSM2493760.RNAseq.RNAseq | Atha.Col.0.root.GC.Alight.Rep3.GSM2493761.RNAseq.RNAseq | Atha.Col.0.root.GC.dark.Rep1.GSM2493768.RNAseq.RNAseq | Atha.Col.0.root.GC.dark.Rep2.GSM2493769.RNAseq.RNAseq | Atha.Col.0.root.GC.dark.Rep3.GSM2493770.RNAseq.RNAseq | Atha.Ws.root.GC.Alight.Rep1.GSM2493762.RNAseq.RNAseq | Atha.Ws.root.GC.Alight.Rep2.GSM2493763.RNAseq.RNAseq | Atha.Ws.root.GC.Alight.Rep3.GSM2493764.RNAseq.RNAseq | Atha.Ws.root.GC.dark.Rep1.GSM2493771.RNAseq.RNAseq | Atha.Ws.root.GC.dark.Rep2.GSM2493772.RNAseq.RNAseq | Atha.Ws.root.GC.dark.Rep3.GSM2493773.RNAseq.RNAseq | Atha.Col.0.PhyD.root.GC.Alight.Rep1.GSM2493765.RNAseq.RNAseq | Atha.Col.0.PhyD.root.GC.Alight.Rep2.GSM2493766.RNAseq.RNAseq | Atha.Col.0.PhyD.root.GC.Alight.Rep3.GSM2493767.RNAseq.RNAseq | Atha.Col.0.PhyD.root.GC.dark.Rep1.GSM2493774.RNAseq.RNAseq | Atha.Col.0.PhyD.root.GC.dark.Rep2.GSM2493775.RNAseq.RNAseq | Atha.Col.0.PhyD.root.GC.dark.Rep3.GSM2493776.RNAseq.RNAseq | Atha.Col.0.root.FLT.Alight.Rep1.GSM2493777.RNAseq.RNAseq | Atha.Col.0.root.FLT.Alight.Rep2.GSM2493778.RNAseq.RNAseq | Atha.Col.0.root.FLT.Alight.Rep3.GSM2493779.RNAseq.RNAseq | Atha.Col.0.root.FLT.dark.Rep1.GSM2493786.RNAseq.RNAseq | Atha.Col.0.root.FLT.dark.Rep2.GSM2493787.RNAseq.RNAseq | Atha.Col.0.root.FLT.dark.Rep3.GSM2493788.RNAseq.RNAseq | Atha.Ws.root.FLT.Alight.Rep1.GSM2493780.RNAseq.RNAseq | Atha.Ws.root.FLT.Alight.Rep2.GSM2493781.RNAseq.RNAseq | Atha.Ws.root.FLT.Alight.Rep3.GSM2493782.RNAseq.RNAseq | Atha.Ws.root.FLT.dark.Rep1.GSM2493789.RNAseq.RNAseq | Atha.Ws.root.FLT.dark.Rep2.GSM2493790.RNAseq.RNAseq | Atha.Ws.root.FLT.dark.Rep3.GSM2493791.RNAseq.RNAseq | Atha.Col.0.PhyD.root.FLT.Alight.Rep1.GSM2493783.RNAseq.RNAseq | Atha.Col.0.PhyD.root.FLT.Alight.Rep2.GSM2493784.RNAseq.RNAseq | Atha.Col.0.PhyD.root.FLT.Alight.Rep3.GSM2493785.RNAseq.RNAseq | Atha.Col.0.PhyD.root.FLT.dark.Rep1.GSM2493792.RNAseq.RNAseq | Atha.Col.0.PhyD.root.FLT.dark.Rep2.GSM2493793.RNAseq.RNAseq | Atha.Col.0.PhyD.root.FLT.dark.Rep3.GSM2493794.RNAseq.RNAseq |
| Sample.Id | ||||||||||||||||||||||||||||||||||||
| Sample.Name | Atha_Col-0_root_GC_Alight_Rep1_GSM2493759 | Atha_Col-0_root_GC_Alight_Rep2_GSM2493760 | Atha_Col-0_root_GC_Alight_Rep3_GSM2493761 | Atha_Col-0_root_GC_dark_Rep1_GSM2493768 | Atha_Col-0_root_GC_dark_Rep2_GSM2493769 | Atha_Col-0_root_GC_dark_Rep3_GSM2493770 | Atha_Ws_root_GC_Alight_Rep1_GSM2493762 | Atha_Ws_root_GC_Alight_Rep2_GSM2493763 | Atha_Ws_root_GC_Alight_Rep3_GSM2493764 | Atha_Ws_root_GC_dark_Rep1_GSM2493771 | Atha_Ws_root_GC_dark_Rep2_GSM2493772 | Atha_Ws_root_GC_dark_Rep3_GSM2493773 | Atha_Col-0-PhyD_root_GC_Alight_Rep1_GSM2493765 | Atha_Col-0-PhyD_root_GC_Alight_Rep2_GSM2493766 | Atha_Col-0-PhyD_root_GC_Alight_Rep3_GSM2493767 | Atha_Col-0-PhyD_root_GC_dark_Rep1_GSM2493774 | Atha_Col-0-PhyD_root_GC_dark_Rep2_GSM2493775 | Atha_Col-0-PhyD_root_GC_dark_Rep3_GSM2493776 | Atha_Col-0_root_FLT_Alight_Rep1_GSM2493777 | Atha_Col-0_root_FLT_Alight_Rep2_GSM2493778 | Atha_Col-0_root_FLT_Alight_Rep3_GSM2493779 | Atha_Col-0_root_FLT_dark_Rep1_GSM2493786 | Atha_Col-0_root_FLT_dark_Rep2_GSM2493787 | Atha_Col-0_root_FLT_dark_Rep3_GSM2493788 | Atha_Ws_root_FLT_Alight_Rep1_GSM2493780 | Atha_Ws_root_FLT_Alight_Rep2_GSM2493781 | Atha_Ws_root_FLT_Alight_Rep3_GSM2493782 | Atha_Ws_root_FLT_dark_Rep1_GSM2493789 | Atha_Ws_root_FLT_dark_Rep2_GSM2493790 | Atha_Ws_root_FLT_dark_Rep3_GSM2493791 | Atha_Col-0-PhyD_root_FLT_Alight_Rep1_GSM2493783 | Atha_Col-0-PhyD_root_FLT_Alight_Rep2_GSM2493784 | Atha_Col-0-PhyD_root_FLT_Alight_Rep3_GSM2493785 | Atha_Col-0-PhyD_root_FLT_dark_Rep1_GSM2493792 | Atha_Col-0-PhyD_root_FLT_dark_Rep2_GSM2493793 | Atha_Col-0-PhyD_root_FLT_dark_Rep3_GSM2493794 |
| GLDS | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 | 120 |
| Accession | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 | GLDS-120 |
| Hardware | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish | Petri dish |
| Tissue | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots | Roots |
| Age | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days | 11 days |
| Organism | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana | Arabidopsis thaliana |
| Ecotype | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | WS-0 | WS-0 | WS-0 | WS-0 | WS-0 | WS-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | WS-0 | WS-0 | WS-0 | WS-0 | WS-0 | WS-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 | Col-0 |
| Genotype | WT | WT | WT | WT | WT | WT | WT | WT | WT | WT | WT | WT | PhyD | PhyD | PhyD | PhyD | PhyD | PhyD | WT | WT | WT | WT | WT | WT | WT | WT | WT | WT | WT | WT | PhyD | PhyD | PhyD | PhyD | PhyD | PhyD |
| Variety | Col-0 WT | Col-0 WT | Col-0 WT | Col-0 WT | Col-0 WT | Col-0 WT | WS-0 WT | WS-0 WT | WS-0 WT | WS-0 WT | WS-0 WT | WS-0 WT | Col-0 PhyD | Col-0 PhyD | Col-0 PhyD | Col-0 PhyD | Col-0 PhyD | Col-0 PhyD | Col-0 WT | Col-0 WT | Col-0 WT | Col-0 WT | Col-0 WT | Col-0 WT | WS-0 WT | WS-0 WT | WS-0 WT | WS-0 WT | WS-0 WT | WS-0 WT | Col-0 PhyD | Col-0 PhyD | Col-0 PhyD | Col-0 PhyD | Col-0 PhyD | Col-0 PhyD |
| Radiation | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Background Earth | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation | Cosmic radiation |
| Gravity | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Terrestrial | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity | Microgravity |
| Developmental | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots | 11 day old seedling roots |
| Time.series.or.Concentration.gradient | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point | Single time point |
| Light | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | 4-6 umoles m-2 s-1 total light | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown | Light-activated for 4 hours, then dark-grown |
| Analysis.Light | Alight | Alight | Alight | Dark | Dark | Dark | Alight | Alight | Alight | Dark | Dark | Dark | Alight | Alight | Alight | Dark | Dark | Dark | Alight | Alight | Alight | Dark | Dark | Dark | Alight | Alight | Alight | Dark | Dark | Dark | Alight | Alight | Alight | Dark | Dark | Dark |
| Assay..RNAseq. | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling | RNAseq Transcription Profiling |
| Temperature | ||||||||||||||||||||||||||||||||||||
| Treatment.type | ||||||||||||||||||||||||||||||||||||
| Treatment.intensity | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
| Treament.timing | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X | X |
| Preservation.Method. | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater | RNAlater |
readData.out <- readData(inputFile)
## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors
kable( head(readData.out$data) ) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%")
| Col0_GC_Alight_Rep1 | Col0_GC_Alight_Rep2 | Col0_GC_Alight_Rep3 | Col0_GC_dark_Rep1 | Col0_GC_dark_Rep2 | Col0_GC_dark_Rep3 | Ws_GC_Alight_Rep1 | Ws_GC_Alight_Rep2 | Ws_GC_Alight_Rep3 | Ws_GC_dark_Rep1 | Ws_GC_dark_Rep2 | Ws_GC_dark_Rep3 | Col0PhyD_GC_Alight_Rep1 | Col0PhyD_GC_Alight_Rep2 | Col0PhyD_GC_Alight_Rep3 | Col0PhyD_GC_dark_Rep1 | Col0PhyD_GC_dark_Rep2 | Col0PhyD_GC_dark_Rep3 | Col0_FLT_Alight_Rep1 | Col0_FLT_Alight_Rep2 | Col0_FLT_Alight_Rep3 | Col0_FLT_dark_Rep1 | Col0_FLT_dark_Rep2 | Col0_FLT_dark_Rep3 | Ws_FLT_Alight_Rep1 | Ws_FLT_Alight_Rep2 | Ws_FLT_Alight_Rep3 | Ws_FLT_dark_Rep1 | Ws_FLT_dark_Rep2 | Ws_FLT_dark_Rep3 | Col0PhyD_FLT_Alight_Rep1 | Col0PhyD_FLT_Alight_Rep2 | Col0PhyD_FLT_Alight_Rep3 | Col0PhyD_FLT_dark_Rep1 | Col0PhyD_FLT_dark_Rep2 | Col0PhyD_FLT_dark_Rep3 | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| AT1G07590 | 14.09484 | 15.82643 | 16.00050 | 13.10404 | 13.51777 | 14.64386 | 13.409439 | 15.77315 | 14.82674 | 8.734572 | 12.853189 | 14.49060 | 14.30307 | 16.42429 | 16.25823 | 14.93434 | 14.023780 | 13.652232 | 13.06820 | 13.47644 | 15.85437 | 14.53257 | 12.546514 | 16.29378 | 13.70761 | 17.15691 | 15.84185 | 11.771773 | 15.17731 | 15.44411 | 15.63005 | 16.46416 | 16.53664 | 16.16638 | 14.22419 | 11.227882 |
| AT1G21310 | 13.82237 | 12.89321 | 13.59194 | 12.69178 | 11.84638 | 13.57377 | 11.609280 | 14.87147 | 13.40320 | 10.803775 | 11.668910 | 12.93797 | 12.21651 | 15.52722 | 14.64023 | 14.21443 | 13.702426 | 13.487243 | 13.86935 | 13.89505 | 14.02481 | 14.15226 | 13.295761 | 15.67999 | 14.01774 | 15.40720 | 14.53493 | 13.029378 | 14.92947 | 14.70538 | 14.61414 | 13.92094 | 14.68044 | 14.58744 | 13.84959 | 11.987155 |
| AT2G33830 | 13.00360 | 12.70793 | 13.19989 | 11.07625 | 11.44428 | 12.10500 | 11.605670 | 13.01332 | 13.23629 | 6.342765 | 8.041026 | 10.62547 | 13.12869 | 14.63728 | 13.86356 | 12.00093 | 9.571015 | 8.582187 | 13.84084 | 13.54377 | 14.43678 | 13.47765 | 11.086524 | 14.73928 | 13.32348 | 14.63064 | 13.90582 | 9.399696 | 12.33273 | 12.11427 | 14.45015 | 14.83492 | 14.74970 | 13.46973 | 13.62021 | 13.043726 |
| AT1G07610 | 12.08104 | 14.30673 | 14.23944 | 10.40031 | 11.39977 | 12.30921 | 9.268934 | 12.67998 | 11.15489 | 4.495592 | 9.733672 | 10.63264 | 11.22988 | 14.58783 | 14.11140 | 12.85493 | 11.888352 | 11.502633 | 10.64115 | 11.46993 | 13.77730 | 12.79971 | 9.080162 | 14.60663 | 10.27736 | 13.91128 | 12.58584 | 8.510065 | 11.83719 | 12.25284 | 13.89512 | 14.26232 | 14.34338 | 13.98226 | 11.39071 | 6.943481 |
| AT5G03240 | 13.20130 | 13.12291 | 13.32156 | 11.49666 | 11.57663 | 13.03192 | 12.702830 | 13.73541 | 14.16480 | 10.261950 | 10.374225 | 11.62274 | 13.07120 | 14.91590 | 14.53655 | 13.45543 | 11.608011 | 11.671690 | 12.73701 | 13.21551 | 13.74191 | 12.73065 | 10.975705 | 12.96365 | 12.31093 | 14.01545 | 13.06204 | 10.566490 | 12.53392 | 12.64681 | 13.26962 | 14.37130 | 14.68130 | 13.65752 | 12.14785 | 12.731019 |
| AT2G45960 | 14.76921 | 14.16179 | 14.40573 | 12.98223 | 12.07059 | 13.29898 | 13.412024 | 14.52394 | 14.19108 | 11.907155 | 12.186793 | 12.66575 | 12.72364 | 15.00718 | 14.16692 | 13.92458 | 12.483819 | 12.222020 | 13.90170 | 13.63596 | 14.27782 | 13.88254 | 12.522675 | 13.61255 | 14.13872 | 13.88720 | 14.02430 | 11.971582 | 13.47262 | 13.65144 | 13.90907 | 13.79361 | 14.08793 | 13.30008 | 12.89654 | 12.072701 |
readSampleInfo.out <- readSampleInfo(sampleInfoFile)
kable( readSampleInfo.out ) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%")
| Gravity | Variety | Light | |
|---|---|---|---|
| Col0_GC_Alight_Rep1 | Terrestrial | Col0 WT | Alight |
| Col0_GC_Alight_Rep2 | Terrestrial | Col0 WT | Alight |
| Col0_GC_Alight_Rep3 | Terrestrial | Col0 WT | Alight |
| Col0_GC_dark_Rep1 | Terrestrial | Col0 WT | Dark |
| Col0_GC_dark_Rep2 | Terrestrial | Col0 WT | Dark |
| Col0_GC_dark_Rep3 | Terrestrial | Col0 WT | Dark |
| Ws_GC_Alight_Rep1 | Terrestrial | WS0 WT | Alight |
| Ws_GC_Alight_Rep2 | Terrestrial | WS0 WT | Alight |
| Ws_GC_Alight_Rep3 | Terrestrial | WS0 WT | Alight |
| Ws_GC_dark_Rep1 | Terrestrial | WS0 WT | Dark |
| Ws_GC_dark_Rep2 | Terrestrial | WS0 WT | Dark |
| Ws_GC_dark_Rep3 | Terrestrial | WS0 WT | Dark |
| Col0PhyD_GC_Alight_Rep1 | Terrestrial | Col0 PhyD | Alight |
| Col0PhyD_GC_Alight_Rep2 | Terrestrial | Col0 PhyD | Alight |
| Col0PhyD_GC_Alight_Rep3 | Terrestrial | Col0 PhyD | Alight |
| Col0PhyD_GC_dark_Rep1 | Terrestrial | Col0 PhyD | Dark |
| Col0PhyD_GC_dark_Rep2 | Terrestrial | Col0 PhyD | Dark |
| Col0PhyD_GC_dark_Rep3 | Terrestrial | Col0 PhyD | Dark |
| Col0_FLT_Alight_Rep1 | Microgravity | Col0 WT | Alight |
| Col0_FLT_Alight_Rep2 | Microgravity | Col0 WT | Alight |
| Col0_FLT_Alight_Rep3 | Microgravity | Col0 WT | Alight |
| Col0_FLT_dark_Rep1 | Microgravity | Col0 WT | Dark |
| Col0_FLT_dark_Rep2 | Microgravity | Col0 WT | Dark |
| Col0_FLT_dark_Rep3 | Microgravity | Col0 WT | Dark |
| Ws_FLT_Alight_Rep1 | Microgravity | WS0 WT | Alight |
| Ws_FLT_Alight_Rep2 | Microgravity | WS0 WT | Alight |
| Ws_FLT_Alight_Rep3 | Microgravity | WS0 WT | Alight |
| Ws_FLT_dark_Rep1 | Microgravity | WS0 WT | Dark |
| Ws_FLT_dark_Rep2 | Microgravity | WS0 WT | Dark |
| Ws_FLT_dark_Rep3 | Microgravity | WS0 WT | Dark |
| Col0PhyD_FLT_Alight_Rep1 | Microgravity | Col0 PhyD | Alight |
| Col0PhyD_FLT_Alight_Rep2 | Microgravity | Col0 PhyD | Alight |
| Col0PhyD_FLT_Alight_Rep3 | Microgravity | Col0 PhyD | Alight |
| Col0PhyD_FLT_dark_Rep1 | Microgravity | Col0 PhyD | Dark |
| Col0PhyD_FLT_dark_Rep2 | Microgravity | Col0 PhyD | Dark |
| Col0PhyD_FLT_dark_Rep3 | Microgravity | Col0 PhyD | Dark |
input_selectOrg ="NEW"
input_selectGO <- 'GOBP' #Gene set category
input_noIDConversion = TRUE
allGeneInfo.out <- geneInfo(geneInfoFile)
converted.out = NULL
convertedData.out <- convertedData()
nGenesFilter()
## [1] "16156 genes in 36 samples. 16155 genes passed filter.\n Original gene IDs used."
convertedCounts.out <- convertedCounts() # converted counts, just for compatibility
# Read counts per library
parDefault = par()
par(mar=c(12,4,2,2))
# barplot of total read counts
x <- readData.out$rawCounts
groups = as.factor( detectGroups(colnames(x ) ) )
if(nlevels(groups)<=1 | nlevels(groups) >20 )
col1 = 'green' else
col1 = rainbow(nlevels(groups))[ groups ]
barplot( colSums(x)/1e6,
col=col1,las=3, main="Total read counts (millions)")
readCountsBias() # detecting bias in sequencing depth
## [1] 0.05123677
## [1] 0.5460606
## [1] 0.2013552
## [1] 0.3019591
## [1] "No bias detected"
# Box plot
x = readData.out$data
boxplot(x, las = 2, col=col1,
ylab='Transformed expression levels',
main='Distribution of transformed data')
#Density plot
par(parDefault)
## Warning in par(parDefault): graphical parameter "cin" cannot be set
## Warning in par(parDefault): graphical parameter "cra" cannot be set
## Warning in par(parDefault): graphical parameter "csi" cannot be set
## Warning in par(parDefault): graphical parameter "cxy" cannot be set
## Warning in par(parDefault): graphical parameter "din" cannot be set
## Warning in par(parDefault): graphical parameter "page" cannot be set
densityPlot()
# Scatter plot of the first two samples
plot(x[,1:2],xlab=colnames(x)[1],ylab=colnames(x)[2],
main='Scatter plot of first two samples')
####plot gene or gene family
input_selectOrg ="BestMatch"
input_geneSearch <- 'HOXA' #Gene ID for searching
genePlot()
## NULL
input_useSD <- 'FALSE' #Use standard deviation instead of standard error in error bar?
geneBarPlotError()
## NULL
# hierarchical clustering tree
x <- readData.out$data
maxGene <- apply(x,1,max)
# remove bottom 25% lowly expressed genes, which inflate the PPC
x <- x[which(maxGene > quantile(maxGene)[1] ) ,]
plot(as.dendrogram(hclust2( dist2(t(x)))), ylab="1 - Pearson C.C.", type = "rectangle")
#Correlation matrix
input_labelPCC <- TRUE #Show correlation coefficient?
correlationMatrix()
# Parameters for heatmap
input_nGenes <- 1000 #Top genes for heatmap
input_geneCentering <- TRUE #centering genes ?
input_sampleCentering <- FALSE #Center by sample?
input_geneNormalize <- FALSE #Normalize by gene?
input_sampleNormalize <- FALSE #Normalize by sample?
input_noSampleClustering <- FALSE #Use original sample order
input_heatmapCutoff <- 4 #Remove outliers beyond number of SDs
input_distFunctions <- 1 #which distant funciton to use
input_hclustFunctions <- 1 #Linkage type
input_heatColors1 <- 1 #Colors
input_selectFactorsHeatmap <- 'Light' #Sample coloring factors
png('heatmap.png', width = 10, height = 15, units = 'in', res = 300)
staticHeatmap()
dev.off()
## png
## 2
[heatmap] (heatmap.png)
heatmapPlotly() # interactive heatmap using Plotly
input_nGenesKNN <- 2000 #Number of genes fro k-Means
input_nClusters <- 4 #Number of clusters
maxGeneClustering = 12000
input_kmeansNormalization <- 'geneMean' #Normalization
input_KmeansReRun <- 0 #Random seed
distributionSD() #Distribution of standard deviations
KmeansNclusters() #Number of clusters
Kmeans.out = Kmeans() #Running K-means
KmeansHeatmap() #Heatmap for k-Means
#Read gene sets for enrichment analysis
sqlite <- dbDriver('SQLite')
input_selectGO3 <- 'GOBP' #Gene set category
input_minSetSize <- 15 #Min gene set size
input_maxSetSize <- 2000 #Max gene set size
GeneSets.out <-readGeneSets( geneSetFile,
convertedData.out, input_selectGO3,input_selectOrg,
c(input_minSetSize, input_maxSetSize) )
# Alternatively, users can use their own GMT files by
#GeneSets.out <- readGMTRobust('somefile.GMT')
results <- KmeansGO() #Enrichment analysis for k-Means clusters
results$adj.Pval <- format( results$adj.Pval,digits=3 )
kable( results, row.names=FALSE) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%")
| Cluster | adj.Pval | Genes | Pathways |
|---|---|---|---|
| A | 2.25e-169 | 236 | Amide biosynthetic process |
| 7.51e-167 | 225 | Translation | |
| 1.76e-166 | 225 | Peptide biosynthetic process | |
| 2.01e-161 | 313 | Organonitrogen compound biosynthetic process | |
| 2.03e-159 | 242 | Cellular amide metabolic process | |
| 4.21e-158 | 226 | Peptide metabolic process | |
| 1.69e-89 | 137 | Ribonucleoprotein complex biogenesis | |
| 5.02e-83 | 206 | Cellular component biogenesis | |
| 1.94e-71 | 109 | Ribosome biogenesis | |
| 1.93e-62 | 95 | Response to cadmium ion | |
| B | 1.41e-14 | 17 | Detoxification |
| 2.90e-14 | 19 | Response to toxic substance | |
| 2.90e-14 | 16 | Drug catabolic process | |
| 2.90e-14 | 15 | Cellular oxidant detoxification | |
| 3.83e-14 | 10 | Water transport | |
| 3.83e-14 | 10 | Fluid transport | |
| 3.83e-14 | 15 | Cellular detoxification | |
| 4.93e-14 | 12 | Hydrogen peroxide catabolic process | |
| 7.79e-14 | 15 | Cellular response to toxic substance | |
| 2.35e-13 | 20 | Response to oxidative stress | |
| C | 1.83e-32 | 129 | Response to abiotic stimulus |
| 2.31e-31 | 83 | Response to inorganic substance | |
| 4.80e-25 | 54 | Response to metal ion | |
| 1.10e-23 | 88 | Cellular catabolic process | |
| 4.30e-23 | 96 | Catabolic process | |
| 5.18e-23 | 45 | Response to cadmium ion | |
| 5.68e-22 | 93 | Response to oxygen-containing compound | |
| 7.79e-21 | 87 | Oxidation-reduction process | |
| 9.68e-21 | 88 | Cellular response to chemical stimulus | |
| 6.58e-19 | 74 | Response to acid chemical | |
| D | 1.66e-16 | 51 | Response to abiotic stimulus |
| 1.66e-16 | 20 | Cellular response to decreased oxygen levels | |
| 1.66e-16 | 43 | Cellular response to chemical stimulus | |
| 1.66e-16 | 20 | Cellular response to oxygen levels | |
| 1.66e-16 | 20 | Cellular response to hypoxia | |
| 7.26e-16 | 38 | Cellular response to stress | |
| 9.22e-16 | 20 | Response to hypoxia | |
| 1.07e-15 | 20 | Response to decreased oxygen levels | |
| 1.07e-15 | 20 | Response to oxygen levels | |
| 2.58e-15 | 39 | Response to external stimulus |
input_seedTSNE <- 0 #Random seed for t-SNE
input_colorGenes <- TRUE #Color genes in t-SNE plot?
tSNEgenePlot() #Plot genes using t-SNE
input_selectFactors <- 'Variety' #Factor coded by color
input_selectFactors2 <- 'Light' #Factor coded by shape
input_tsneSeed2 <- 0 #Random seed for t-SNE
#PCA, MDS and t-SNE plots
PCAplot()
MDSplot()
tSNEplot()
#Read gene sets for pathway analysis using PGSEA on principal components
input_selectGO6 <- 'GOBP'
GeneSets.out <-readGeneSets( geneSetFile,
convertedData.out, input_selectGO6,input_selectOrg,
c(input_minSetSize, input_maxSetSize) )
PCApathway() # Run PGSEA analysis
## Warning: Package 'KEGG.db' is deprecated and will be removed from Bioconductor
## version 3.12
cat( PCA2factor() ) #The correlation between PCs with factors
##
## Correlation between Principal Components (PCs) with factors
## PC1 is correlated with Light (p=5.73e-03).
## PC2 is correlated with Variety (p=2.38e-06).
## PC5 is correlated with Gravity (p=1.07e-05).
input_CountsDEGMethod <- 3 #DESeq2= 3,limma-voom=2,limma-trend=1
input_limmaPval <- 0.1 #FDR cutoff
input_limmaFC <- 2 #Fold-change cutoff
input_selectModelComprions <- 'Gravity: Microgravity vs. Terrestrial' #Selected comparisons
input_selectFactorsModel <- 'Gravity' #Selected comparisons
input_selectInteractions <- NULL #Selected comparisons
input_selectBlockFactorsModel <- NULL #Selected comparisons
factorReferenceLevels.out <- c('Gravity:Terrestrial','Light:Alight')
limma.out <- limma()
## Warning in DESeqDataSet(se, design = design, ignoreRank): some variables in
## design formula are characters, converting to factors
DEG.data.out <- DEG.data()
limma.out$comparisons
## [1] "Microgravity-Terrestrial"
input_selectComparisonsVenn = limma.out$comparisons[1:3] # use first three comparisons
input_UpDownRegulated <- FALSE #Split up and down regulated genes
vennPlot() # Venn diagram
sigGeneStats() # number of DEGs as figure
sigGeneStatsTable() # number of DEGs as table
## Comparisons Up Down
## Microgravity-Terrestrial Microgravity-Terrestrial 77 50
input_selectContrast <- 'Microgravity-Terrestrial' #Selected comparisons
selectedHeatmap.data.out <- selectedHeatmap.data()
selectedHeatmap() # heatmap for DEGs in selected comparison
## $genes
## Col0_GC_Alight_Rep1 Col0_GC_Alight_Rep2 Col0_GC_Alight_Rep3
## AT3G62040 8.104727 11.568320 11.697708
## AT5G05960 7.184797 10.242935 10.254254
## AT5G13930 9.633729 8.863853 9.079192
## AT2G21640 4.220106 5.369623 5.263637
## AT4G31910 8.778767 9.839191 10.017478
## AT3G03780 8.068476 7.514599 7.906864
## AT2G40900 8.348801 9.525778 9.824455
## AT2G41480 6.566055 9.736564 9.515016
## AT5G63850 6.624296 9.016747 9.247347
## AT3G54500 8.967762 8.413979 8.572169
## AT3G02850 7.184797 6.833750 7.084960
## AT5G37260 7.074229 7.992095 8.451734
## AT4G31730 7.094973 8.471031 8.703877
## AT3G23810 6.505365 7.857968 7.333875
## AT3G17609 8.031291 7.545284 7.598275
## AT3G26830 5.582295 6.676309 6.976491
## AT5G05270 7.602012 7.782703 7.717650
## AT2G46830 7.063744 7.213971 7.126162
## AT3G51240 7.895992 7.223490 6.965181
## AT3G09600 7.194441 7.756716 7.796338
## AT5G17300 7.241716 7.814542 8.175731
## AT5G47990 2.000000 2.987502 3.444032
## AT4G01440 2.573281 5.859255 6.369208
## AT4G09950 5.177983 5.225486 5.650070
## AT1G78580 6.624296 6.918234 6.484596
## AT5G50120 5.552608 7.052461 7.491961
## AT3G54820 4.060523 3.981213 4.734235
## AT5G44350 3.973583 5.677282 5.810333
## AT2G47560 2.000000 6.298089 7.185841
## AT3G57020 5.921170 5.531638 5.908068
## AT3G06020 2.000000 6.986908 6.298877
## AT5G08640 5.800066 5.065335 5.784828
## AT3G03770 4.494437 5.262893 4.439601
## AT2G25680 4.142520 3.568275 3.790058
## AT1G30380 4.555580 5.953783 5.758865
## AT3G56730 3.150403 6.185717 6.634906
## AT5G56720 4.060523 4.228145 4.372699
## AT5G64940 6.288384 5.976478 4.885877
## AT2G47460 5.098033 5.784058 5.678047
## AT2G02020 3.676072 3.683106 3.790058
## AT5G50800 2.000000 2.796649 3.156490
## AT4G24670 4.670600 4.372029 4.786574
## AT1G29910 5.360388 6.020824 4.503539
## AT1G11700 2.792319 5.369623 5.931501
## AT4G25830 4.494437 5.147632 5.650070
## AT4G15430 4.494437 4.679226 5.335664
## AT4G26790 3.973583 4.885159 3.568825
## AT1G68585 3.150403 4.438924 4.228798
## AT5G13630 3.973583 5.262893 3.981833
## AT1G62710 2.314931 4.301880 3.981833
## AT3G05880 11.327215 12.203435 11.984178
## AT3G44300 11.440452 11.115770 10.747271
## AT2G26400 5.582295 3.789468 5.023084
## AT3G54040 6.624296 9.213468 9.739051
## AT1G19960 8.318253 9.678921 9.112891
## AT5G23220 8.504212 7.845693 7.777065
## AT5G24530 7.847918 7.906048 8.402275
## AT5G22555 6.988136 7.418421 7.648631
## AT3G56400 7.184797 6.298089 7.009896
## AT5G05500 6.095994 7.975291 8.233434
## AT5G66170 6.872751 7.341832 6.591435
## AT1G56300 8.063223 7.459277 6.796771
## AT1G51420 7.658846 7.763257 7.620072
## AT5G01210 6.156451 5.704726 6.224941
## AT3G21510 6.032891 7.857968 8.406462
## AT5G66780 5.639896 3.443507 2.987914
## AT3G22121 7.323093 4.836365 6.809475
## AT5G07010 8.052657 7.041741 6.822067
## AT5G41280 6.075265 6.545817 6.147010
## AT5G13330 6.680276 6.084888 6.205850
## AT1G49720 7.287490 6.821266 7.289225
## AT3G22120 7.481150 4.564073 5.758865
## AT2G46680 6.095994 6.870564 6.515937
## AT5G15120 6.580837 4.068305 4.564763
## AT3G53160 7.890070 4.502855 4.372699
## AT2G18690 2.000000 4.932356 5.066066
## AT2G15960 4.876320 3.789468 4.439601
## AT3G17790 4.060523 4.885159 5.107804
## AT4G13195 7.063744 4.228145 5.107804
## AT5G02810 7.496823 6.084888 6.316784
## AT4G13390 3.150403 4.836365 5.370373
## AT2G44080 5.459697 5.500658 5.860028
## AT1G12040 3.973583 6.261596 6.106407
## AT1G22770 6.054234 6.368419 6.298877
## AT4G33070 6.442008 5.403514 5.107804
## AT3G52770 5.695286 5.930725 5.784828
## AT4G33980 4.827574 5.591671 5.226228
## AT2G43570 3.300833 5.468998 5.300100
## AT2G36470 4.430589 6.063847 5.732426
## AT1G06460 6.306284 4.502855 5.532397
## AT1G48930 4.614236 5.930725 5.148368
## AT5G48175 4.494437 5.953783 5.931501
## AT5G02230 3.676072 3.789468 4.228798
## AT1G11210 2.573281 5.187084 4.734235
## AT4G12290 5.459697 3.888524 4.228798
## AT5G18470 3.150403 3.789468 3.568825
## AT3G23150 5.253734 4.372029 3.889130
## AT5G57540 2.000000 2.987502 2.987914
## AT5G24470 5.290169 5.147632 4.439601
## AT5G61650 3.782207 3.568275 4.885877
## AT1G02450 2.982442 3.306918 2.987914
## AT5G19790 2.792319 5.976478 4.679927
## AT2G28690 4.777124 4.622798 4.439601
## AT2G05520 2.314931 2.576643 3.790058
## AT2G20520 2.000000 2.000000 3.444032
## AT5G42900 4.430589 4.301880 4.933077
## AT1G54970 2.000000 2.316942 3.156490
## AT5G22270 2.982442 3.789468 2.987914
## AT2G20560 4.555580 4.836365 5.148368
## AT1G28480 2.982442 3.156032 3.307413
## AT3G53800 5.325706 4.978058 4.933077
## AT5G61660 4.142520 3.888524 4.933077
## AT5G18270 3.300833 4.622798 4.885877
## AT3G10040 4.430589 3.981213 3.156490
## AT4G03440 4.555580 5.022356 4.933077
## AT3G04070 2.314931 3.306918 2.987914
## AT3G10710 2.000000 4.502855 3.444032
## AT1G79320 2.000000 3.789468 3.568825
## AT1G64480 2.000000 3.306918 2.987914
## AT3G05930 4.220106 4.068305 5.023084
## AT1G01660 3.300833 4.228145 3.790058
## AT5G25190 2.573281 3.683106 2.797002
## AT4G35180 2.000000 2.000000 2.000000
## AT1G16440 2.000000 3.981213 2.797002
## AT2G46860 2.000000 2.796649 2.576916
## AT1G25240 2.000000 2.316942 2.797002
## AT1G79860 2.314931 2.796649 2.000000
## Ws_GC_Alight_Rep1 Ws_GC_Alight_Rep2 Ws_GC_Alight_Rep3
## AT3G62040 8.612741 8.041874 7.864678
## AT5G05960 7.580363 9.495186 7.621008
## AT5G13930 5.989479 10.560442 6.642980
## AT2G21640 5.138793 4.372448 4.674539
## AT4G31910 8.686364 8.575583 8.227133
## AT3G03780 5.825356 7.410616 7.834058
## AT2G40900 8.832511 8.150684 9.022141
## AT2G41480 6.324211 6.871066 7.169855
## AT5G63850 8.875117 7.846203 9.134463
## AT3G54500 8.710093 8.130581 8.305114
## AT3G02850 8.318510 8.435128 8.624284
## AT5G37260 7.602267 8.346402 8.357727
## AT4G31730 7.666051 6.717809 7.846384
## AT3G23810 5.611622 8.355091 7.711386
## AT3G17609 7.720473 7.987027 7.870725
## AT3G26830 5.216588 5.784540 3.679283
## AT5G05270 7.074482 8.337660 7.119960
## AT2G46830 7.779341 7.105406 7.649425
## AT3G51240 6.908597 8.068535 6.711965
## AT3G09600 7.213790 6.895098 7.236931
## AT5G17300 7.473503 6.704271 6.853033
## AT5G47990 2.792429 5.403984 2.574815
## AT4G01440 5.800308 4.068700 5.142704
## AT4G09950 6.375989 5.187546 6.525247
## AT1G78580 6.920270 6.546314 6.446465
## AT5G50120 4.969359 4.503283 5.878295
## AT3G54820 2.000000 4.503283 2.574815
## AT5G44350 4.923698 7.507332 2.984751
## AT2G47560 5.013619 4.679664 3.884471
## AT3G57020 4.293939 6.834251 4.927529
## AT3G06020 5.013619 3.156318 2.574815
## AT5G08640 4.876545 7.115670 5.102160
## AT3G03770 4.827798 4.679664 4.831589
## AT2G25680 3.437212 3.789837 3.152972
## AT1G30380 5.668097 5.999308 3.884471
## AT3G56730 3.561676 4.503283 3.679283
## AT5G56720 5.394492 3.156318 5.142704
## AT5G64940 6.270506 5.835105 5.556883
## AT2G47460 5.178215 6.262088 5.556883
## AT2G02020 3.973777 3.307227 2.000000
## AT5G50800 3.150546 2.796870 2.984751
## AT4G24670 4.614454 4.885608 5.644194
## AT1G29910 5.668097 4.372448 3.977066
## AT1G11700 4.614454 4.786308 2.984751
## AT4G25830 2.000000 5.107529 2.000000
## AT4G15430 4.220311 3.888903 5.220526
## AT4G26790 4.614454 3.443835 3.977066
## AT1G68585 2.982571 3.789837 4.223777
## AT5G13630 4.725066 3.888903 2.574815
## AT1G62710 4.827798 3.683464 3.679283
## AT3G05880 10.871893 11.963414 11.914083
## AT3G44300 10.834598 10.480302 11.042870
## AT2G26400 6.033136 5.954268 7.809085
## AT3G54040 6.136824 8.662156 8.109331
## AT1G19960 7.937038 9.779657 8.617107
## AT5G23220 7.727134 8.864367 8.700951
## AT5G24530 6.721130 8.020185 8.453502
## AT5G22555 3.437212 8.644544 7.099508
## AT3G56400 6.033136 7.669381 6.725375
## AT5G05500 2.314982 8.665653 4.674539
## AT5G66170 7.375155 7.242845 7.387917
## AT1G56300 6.195639 6.676808 6.256330
## AT1G51420 6.011473 7.802400 7.731462
## AT5G01210 5.800308 6.605773 6.628778
## AT3G21510 5.695526 7.583254 6.901093
## AT5G66780 4.494651 3.789837 4.618146
## AT3G22121 7.602267 6.846627 7.516897
## AT5G07010 6.908597 6.419498 7.169855
## AT5G41280 6.096239 7.821336 7.997721
## AT5G13330 5.098263 7.020560 7.697845
## AT1G49720 6.233558 6.690605 7.777248
## AT3G22120 7.543101 7.315877 7.846384
## AT2G46680 6.341678 6.744509 6.670971
## AT5G15120 4.494651 5.931210 6.292817
## AT3G53160 6.786364 5.954268 6.642980
## AT2G18690 3.150546 5.107529 2.984751
## AT2G15960 4.363992 5.187546 6.397045
## AT3G17790 3.782391 5.263358 5.182140
## AT4G13195 5.944461 5.469470 6.079660
## AT5G02810 6.721130 5.784540 6.363132
## AT4G13390 2.000000 2.796870 2.794295
## AT2G44080 5.013619 7.185538 5.925534
## AT1G12040 2.314982 5.883958 3.152972
## AT1G22770 6.931848 4.978511 6.100393
## AT4G33070 5.800308 5.501131 5.971275
## AT3G52770 4.876545 5.107529 5.142704
## AT4G33980 3.676251 6.085376 5.854082
## AT2G43570 2.314982 4.932807 3.679283
## AT2G36470 3.150546 5.562442 5.102160
## AT1G06460 4.670820 4.503283 5.672161
## AT1G48930 2.314982 5.677761 3.152972
## AT5G48175 3.676251 5.065792 5.398484
## AT5G02230 2.000000 4.978511 4.064076
## AT1G11210 2.982571 4.786308 3.152972
## AT4G12290 5.552846 4.439348 5.495594
## AT5G18470 3.881255 5.403984 3.439996
## AT3G23150 2.792429 4.228553 5.294364
## AT5G57540 2.000000 2.000000 2.000000
## AT5G24470 5.459934 5.621253 6.446465
## AT5G61650 2.573366 4.439348 3.679283
## AT1G02450 2.573366 3.888903 3.564595
## AT5G19790 2.792429 5.022811 2.984751
## AT2G28690 2.000000 3.789837 2.984751
## AT2G05520 2.314982 2.796870 2.000000
## AT2G20520 2.000000 2.000000 2.000000
## AT5G42900 3.973777 4.150840 4.297452
## AT1G54970 2.000000 2.000000 2.000000
## AT5G22270 2.000000 3.307227 2.574815
## AT2G20560 4.725066 4.302294 4.434395
## AT1G28480 3.300988 4.733971 2.574815
## AT3G53800 3.561676 5.107529 4.297452
## AT5G61660 2.573366 4.372448 4.434395
## AT5G18270 2.792429 4.302294 4.146135
## AT3G10040 3.782391 2.987760 3.679283
## AT4G03440 4.060721 5.022811 4.297452
## AT3G04070 3.676251 2.000000 4.880356
## AT3G10710 2.000000 2.796870 2.000000
## AT1G79320 2.000000 5.065792 2.000000
## AT1G64480 2.573366 4.623233 3.679283
## AT3G05930 3.881255 5.225950 4.064076
## AT1G01660 3.782391 4.439348 4.367548
## AT5G25190 2.314982 2.796870 2.574815
## AT4G35180 3.973777 3.307227 3.439996
## AT1G16440 2.314982 2.000000 2.000000
## AT2G46860 2.000000 2.000000 2.000000
## AT1G25240 2.792429 2.576814 2.000000
## AT1G79860 2.000000 2.000000 2.000000
## Col0PhyD_GC_Alight_Rep1 Col0PhyD_GC_Alight_Rep2
## AT3G62040 9.330313 7.396435
## AT5G05960 9.144908 6.563949
## AT5G13930 2.000000 9.057714
## AT2G21640 5.299274 3.157781
## AT4G31910 9.255741 8.268367
## AT3G03780 8.678954 6.733772
## AT2G40900 7.917734 8.650708
## AT2G41480 7.935217 6.354170
## AT5G63850 7.084068 6.066828
## AT3G54500 6.730635 9.170510
## AT3G02850 7.251587 7.746656
## AT5G37260 8.297052 7.344924
## AT4G31730 7.155417 6.897659
## AT3G23810 7.633521 7.188116
## AT3G17609 3.306865 7.600566
## AT3G26830 6.952893 4.070720
## AT5G05270 5.022278 6.405358
## AT2G46830 4.885082 7.362299
## AT3G51240 2.000000 6.470901
## AT3G09600 7.223403 7.657977
## AT5G17300 6.676224 7.118244
## AT5G47990 4.502782 3.685290
## AT4G01440 7.675735 4.152894
## AT4G09950 6.757090 7.600566
## AT1G78580 5.591590 4.441510
## AT5G50120 6.368334 5.406385
## AT3G54820 5.369542 3.570377
## AT5G44350 5.225407 6.679355
## AT2G47560 2.000000 2.317568
## AT3G57020 3.306865 6.693153
## AT3G06020 4.563999 2.317568
## AT5G08640 2.000000 4.566707
## AT3G03770 4.836289 4.887900
## AT2G25680 2.796612 3.570377
## AT1G30380 3.443450 6.720359
## AT3G56730 4.932279 3.983581
## AT5G56720 5.369542 6.354170
## AT5G64940 2.796612 5.837570
## AT2G47460 2.000000 5.956748
## AT2G02020 5.907210 5.025136
## AT5G50800 2.000000 2.000000
## AT4G24670 4.502782 4.980826
## AT1G29910 3.683045 5.439505
## AT1G11700 4.733454 4.304407
## AT4G25830 2.000000 4.980826
## AT4G15430 3.981146 5.265733
## AT4G26790 4.438852 4.505466
## AT1G68585 3.306865 4.625454
## AT5G13630 2.000000 4.681902
## AT1G62710 4.502782 4.736224
## AT3G05880 11.302960 12.551491
## AT3G44300 9.699441 10.824388
## AT2G26400 7.483160 7.001113
## AT3G54040 7.393254 9.594727
## AT1G19960 7.851756 10.250767
## AT5G23220 7.393254 8.845534
## AT5G24530 7.073581 9.431463
## AT5G22555 3.306865 8.978238
## AT3G56400 7.145437 9.398155
## AT5G05500 4.371957 8.792043
## AT5G66170 7.736826 8.295756
## AT1G56300 6.402253 8.357710
## AT1G51420 6.833664 8.555726
## AT5G01210 6.952893 7.012163
## AT3G21510 6.530477 8.211979
## AT5G66780 3.306865 4.625454
## AT3G22121 5.187005 7.138555
## AT5G07010 7.084068 8.231021
## AT5G41280 5.731575 7.486346
## AT5G13330 7.125269 7.798636
## AT1G49720 7.213884 7.370909
## AT3G22120 6.204980 7.327336
## AT2G46680 6.619679 7.087231
## AT5G15120 7.801803 7.772880
## AT3G53160 6.929823 7.107980
## AT2G18690 5.334836 7.867182
## AT2G15960 6.385393 6.246000
## AT3G17790 5.147553 6.087871
## AT4G13195 6.648228 7.273250
## AT5G02810 5.859172 8.039093
## AT4G13390 4.150368 6.989978
## AT2G44080 6.605190 7.370909
## AT1G12040 4.885082 6.978756
## AT1G22770 5.561885 7.023129
## AT4G33070 5.731575 6.188713
## AT3G52770 4.371957 6.129058
## AT4G33980 4.885082 6.578890
## AT2G43570 4.228075 5.761032
## AT2G36470 5.299274 6.747061
## AT1G06460 5.262813 6.371435
## AT1G48930 3.683045 6.336696
## AT5G48175 4.977980 6.354170
## AT5G02230 3.155983 5.189907
## AT1G11210 3.683045 6.246000
## AT4G12290 4.371957 6.169101
## AT5G18470 3.306865 4.625454
## AT3G23150 6.105541 6.188713
## AT5G57540 2.796612 3.890838
## AT5G24470 4.679151 4.566707
## AT5G61650 3.306865 5.837570
## AT1G02450 2.316924 2.797995
## AT5G19790 2.316924 5.302202
## AT2G28690 3.443450 4.788575
## AT2G05520 5.299274 4.230639
## AT2G20520 2.316924 2.000000
## AT5G42900 4.563999 5.503548
## AT1G54970 2.000000 2.000000
## AT5G22270 4.977980 4.304407
## AT2G20560 4.228075 5.707653
## AT1G28480 2.000000 6.608315
## AT3G53800 5.591590 5.109873
## AT5G61660 2.000000 5.439505
## AT5G18270 4.885082 5.228318
## AT3G10040 6.166023 3.791722
## AT4G03440 4.679151 4.230639
## AT3G04070 4.622723 3.791722
## AT3G10710 2.316924 4.304407
## AT1G79320 2.796612 3.308808
## AT1G64480 2.000000 2.577688
## AT3G05930 3.981146 4.304407
## AT1G01660 3.443450 3.308808
## AT5G25190 3.981146 2.000000
## AT4G35180 2.000000 2.000000
## AT1G16440 2.796612 2.797995
## AT2G46860 2.796612 2.317568
## AT1G25240 2.796612 2.000000
## AT1G79860 2.000000 2.000000
## Col0PhyD_GC_Alight_Rep3 Col0_FLT_Alight_Rep1 Col0_FLT_Alight_Rep2
## AT3G62040 9.894806 7.136576 6.996681
## AT5G05960 10.000006 4.486833 5.797668
## AT5G13930 9.251930 2.000000 2.314424
## AT2G21640 4.507339 4.135370 3.971658
## AT4G31910 8.946281 8.566906 8.713985
## AT3G03780 6.899856 6.827330 7.029320
## AT2G40900 9.425467 6.315177 7.112914
## AT2G41480 6.595856 3.874333 4.966879
## AT5G63850 8.595251 7.415879 7.229869
## AT3G54500 9.008396 6.297503 6.650077
## AT3G02850 8.983308 5.935570 7.040038
## AT5G37260 8.595251 4.915445 5.692902
## AT4G31730 8.406834 5.740067 5.772181
## AT3G23810 6.911725 6.243141 6.390135
## AT3G17609 8.209421 3.295345 3.559797
## AT3G26830 6.025932 4.486833 4.492313
## AT5G05270 7.302762 4.769227 5.095752
## AT2G46830 8.046723 3.295345 2.791227
## AT3G51240 7.256974 2.977881 2.314424
## AT3G09600 7.905477 3.966694 4.612075
## AT5G17300 7.519923 4.356334 3.879184
## AT5G47990 4.841048 2.000000 3.435419
## AT4G01440 5.536611 3.874333 5.918758
## AT4G09950 6.722546 5.352042 5.871534
## AT1G78580 6.722546 6.224555 5.822713
## AT5G50120 6.923497 4.769227 4.612075
## AT3G54820 2.990203 2.000000 4.291676
## AT5G44350 5.958875 3.145328 4.140522
## AT2G47560 6.303256 2.313121 2.314424
## AT3G57020 6.131201 4.356334 2.791227
## AT3G06020 4.982811 2.000000 2.000000
## AT5G08640 5.191931 2.788417 2.000000
## AT3G03770 4.790519 3.775652 4.722653
## AT2G25680 3.985279 2.977881 4.058559
## AT1G30380 6.248153 2.570255 2.981167
## AT3G56730 5.981575 2.788417 2.791227
## AT5G56720 3.793339 3.295345 3.879184
## AT5G64940 5.682300 3.145328 4.361702
## AT2G47460 6.151363 2.570255 2.791227
## AT2G02020 5.958875 4.212847 3.879184
## AT5G50800 4.376422 2.000000 2.000000
## AT4G24670 5.374540 4.547908 4.722653
## AT1G29910 4.507339 2.000000 3.435419
## AT1G11700 5.596664 2.788417 3.435419
## AT4G25830 5.267770 2.570255 2.572435
## AT4G15430 4.841048 3.431221 3.559797
## AT4G26790 4.072452 3.669723 2.572435
## AT1G68585 5.441569 2.570255 2.791227
## AT5G13630 5.152462 2.313121 2.572435
## AT1G62710 3.892499 2.570255 3.435419
## AT3G05880 12.235679 11.412351 11.785893
## AT3G44300 10.474249 12.045572 11.398331
## AT2G26400 5.596664 8.850617 9.217365
## AT3G54040 9.593308 6.671388 8.397157
## AT1G19960 9.439883 8.427604 8.848106
## AT5G23220 7.715420 10.195167 10.163114
## AT5G24530 8.937600 8.514319 8.599096
## AT5G22555 7.980648 8.606921 8.602715
## AT3G56400 7.715420 7.750650 8.205766
## AT5G05500 6.875822 7.649780 8.627799
## AT5G66170 6.667608 8.369577 7.355317
## AT1G56300 6.839002 8.610504 8.266352
## AT1G51420 7.456517 8.798163 8.454365
## AT5G01210 7.869416 6.956833 8.350561
## AT3G21510 7.881537 7.456265 7.724344
## AT5G66780 2.990203 5.602892 5.391919
## AT3G22121 7.646065 7.571052 8.388796
## AT5G07010 7.311747 8.621200 8.132543
## AT5G41280 6.958247 8.378011 7.690730
## AT5G13330 6.639334 7.763582 7.795649
## AT1G49720 7.440220 8.431661 8.652455
## AT3G22120 7.320677 7.348813 7.494297
## AT2G46680 6.489003 6.279609 6.321510
## AT5G15120 5.111882 6.511933 6.373283
## AT3G53160 5.152462 7.464208 7.509801
## AT2G18690 5.839684 6.685046 5.895339
## AT2G15960 5.267770 6.066565 5.425005
## AT3G17790 5.111882 5.791482 5.550245
## AT4G13195 6.722546 7.832706 7.968307
## AT5G02810 7.130643 7.391093 7.826930
## AT4G13390 3.159035 5.544149 7.462780
## AT2G44080 5.339821 7.022859 6.846030
## AT1G12040 4.507339 6.024208 7.248472
## AT1G22770 5.912374 7.731032 7.776549
## AT4G33070 6.068966 7.251192 6.882218
## AT3G52770 5.536611 5.208104 4.553436
## AT4G33980 5.935812 5.958246 6.093562
## AT2G43570 5.709752 4.769227 4.612075
## AT2G36470 6.303256 5.317381 6.303831
## AT1G06460 5.789107 6.629618 6.321510
## AT1G48930 4.790519 4.769227 6.212033
## AT5G48175 5.566950 6.107714 6.192951
## AT5G02230 4.683821 4.769227 4.361702
## AT1G11210 4.841048 5.245457 3.674297
## AT4G12290 5.596664 6.465202 6.321510
## AT5G18470 3.446951 5.317381 6.249456
## AT3G23150 4.376422 6.814960 6.963285
## AT5G57540 2.000000 2.000000 5.550245
## AT5G24470 5.763137 6.433185 6.548647
## AT5G61650 4.306221 4.053496 5.847330
## AT1G02450 3.571885 3.669723 4.058559
## AT5G19790 3.686857 4.212847 6.212033
## AT2G28690 4.232428 5.451291 5.692902
## AT2G05520 3.892499 4.053496 4.140522
## AT2G20520 2.000000 2.000000 5.941802
## AT5G42900 5.152462 5.602892 5.214051
## AT1G54970 2.000000 2.788417 5.579927
## AT5G22270 2.990203 3.555395 4.428485
## AT2G20560 4.376422 3.775652 4.361702
## AT1G28480 2.578438 2.570255 2.572435
## AT3G53800 5.191931 6.433185 6.051806
## AT5G61660 4.232428 3.775652 4.966879
## AT5G18270 5.736692 4.053496 5.579927
## AT3G10040 4.738156 4.868333 5.519940
## AT4G03440 5.267770 5.865324 5.609011
## AT3G04070 3.446951 4.486833 4.428485
## AT3G10710 2.318017 2.788417 6.249456
## AT1G79320 4.443365 4.716998 3.559797
## AT1G64480 3.793339 2.000000 2.981167
## AT3G05930 3.793339 4.053496 3.780375
## AT1G01660 2.990203 4.053496 3.148984
## AT5G25190 2.000000 4.135370 3.559797
## AT4G35180 2.000000 2.977881 3.559797
## AT1G16440 2.990203 2.977881 4.966879
## AT2G46860 2.000000 2.313121 2.572435
## AT1G25240 2.000000 2.000000 3.879184
## AT1G79860 2.000000 2.000000 2.981167
## Col0_FLT_Alight_Rep3 Ws_FLT_Alight_Rep1 Ws_FLT_Alight_Rep2
## AT3G62040 5.137538 6.196179 7.756117
## AT5G05960 6.883597 6.342221 7.307486
## AT5G13930 2.000000 2.000000 2.000000
## AT2G21640 4.723864 5.098768 5.039530
## AT4G31910 7.154349 7.166122 6.901539
## AT3G03780 7.725745 7.233193 6.971920
## AT2G40900 8.113780 6.596266 7.971832
## AT2G41480 4.875322 5.057064 6.708921
## AT5G63850 6.719768 6.748128 8.256631
## AT3G54500 6.094906 6.681075 7.134173
## AT3G02850 7.259075 5.749396 6.223578
## AT5G37260 6.115340 6.215264 6.144523
## AT4G31730 6.155361 6.157236 7.715668
## AT3G23810 6.408154 5.553369 5.124381
## AT3G17609 3.781387 5.178723 5.609626
## AT3G26830 5.252700 2.000000 4.243559
## AT5G05270 5.773505 4.364452 6.223578
## AT2G46830 4.292813 5.139299 3.995850
## AT3G51240 3.560741 2.982853 2.000000
## AT3G09600 5.215325 4.969858 3.455911
## AT5G17300 4.493487 4.143163 3.166852
## AT5G47990 2.981872 2.000000 2.000000
## AT4G01440 4.219199 3.150860 4.695757
## AT4G09950 3.436320 4.924194 3.803403
## AT1G78580 3.880224 4.143163 5.972096
## AT5G50120 3.781387 3.881671 4.995157
## AT3G54820 2.791830 3.437572 3.995850
## AT5G44350 5.798994 3.881671 3.166852
## AT2G47560 2.314704 2.573554 2.583119
## AT3G57020 2.791830 3.150860 2.000000
## AT3G06020 2.314704 2.315094 2.000000
## AT5G08640 2.000000 2.000000 2.583119
## AT3G03770 4.429647 4.061155 3.803403
## AT2G25680 3.300147 3.150860 3.581274
## AT1G30380 3.560741 3.676643 3.455911
## AT3G56730 3.675278 2.000000 3.455911
## AT5G56720 3.300147 2.982853 2.583119
## AT5G64940 2.572902 4.220759 2.000000
## AT2G47460 3.300147 2.315094 3.581274
## AT2G02020 2.791830 2.000000 2.000000
## AT5G50800 2.000000 2.000000 3.581274
## AT4G24670 3.436320 3.881671 2.583119
## AT1G29910 2.981872 3.676643 3.318609
## AT1G11700 2.791830 2.982853 5.082579
## AT4G25830 2.572902 2.000000 2.583119
## AT4G15430 3.436320 2.000000 2.320823
## AT4G26790 3.300147 2.792670 2.997235
## AT1G68585 3.436320 2.315094 4.243559
## AT5G13630 2.572902 2.573554 2.000000
## AT1G62710 2.572902 3.301327 3.995850
## AT3G05880 12.943849 12.092880 13.852058
## AT3G44300 11.511421 11.963066 10.585065
## AT2G26400 8.780824 10.331928 9.719004
## AT3G54040 10.173091 8.185137 11.521948
## AT1G19960 10.193656 9.379332 11.221487
## AT5G23220 10.069555 10.415780 9.447766
## AT5G24530 10.132313 8.620482 9.545240
## AT5G22555 8.946798 9.707130 10.199054
## AT3G56400 9.864534 7.971667 8.256631
## AT5G05500 8.909256 9.383556 9.964592
## AT5G66170 9.048593 8.641798 9.184326
## AT1G56300 8.994463 7.971667 7.814741
## AT1G51420 8.784019 8.375301 7.251997
## AT5G01210 8.891594 7.551189 8.756066
## AT3G21510 8.173465 8.524291 9.358632
## AT5G66780 4.292813 5.722971 3.318609
## AT3G22121 6.975885 8.740605 9.194174
## AT5G07010 9.156058 7.010951 6.437662
## AT5G41280 7.952779 9.128135 8.429156
## AT5G13330 8.381797 8.287864 7.858745
## AT1G49720 8.712049 8.175425 8.408157
## AT3G22120 7.657714 8.524291 8.840002
## AT2G46680 9.246838 6.324754 7.701929
## AT5G15120 7.339442 5.395009 8.742708
## AT3G53160 7.924108 6.909149 6.533861
## AT2G18690 8.299361 7.350040 5.387309
## AT2G15960 7.083517 6.734965 7.988904
## AT3G17790 7.114300 5.217098 8.886294
## AT4G13195 6.733053 6.812204 6.609400
## AT5G02810 7.952779 7.588260 7.695010
## AT4G13390 5.920091 5.553369 6.594605
## AT2G44080 7.313147 7.489820 8.270660
## AT1G12040 6.964667 6.920822 7.412446
## AT1G22770 7.894856 6.490579 7.039026
## AT4G33070 7.083517 7.126347 7.971832
## AT3G52770 5.097013 5.139299 6.387045
## AT4G33980 7.705670 6.521573 7.960337
## AT2G43570 7.083517 4.143163 6.352286
## AT2G36470 7.144441 5.460453 7.103149
## AT1G06460 6.759260 5.800838 5.949018
## AT1G48930 6.679165 6.474828 7.478404
## AT5G48175 6.930479 6.458904 6.749557
## AT5G02230 6.594362 4.924194 4.243559
## AT1G11210 6.930479 2.792670 6.280150
## AT4G12290 6.733053 5.967680 5.827743
## AT5G18470 5.747557 5.428102 6.223578
## AT3G23150 6.975885 5.944995 6.695117
## AT5G57540 3.972721 4.828289 4.580350
## AT5G24470 6.269163 6.289172 5.352557
## AT5G61650 5.638833 5.553369 4.949376
## AT1G02450 4.776137 6.176839 5.242975
## AT5G19790 4.723864 5.850508 6.404116
## AT2G28690 6.608846 5.696053 6.060884
## AT2G05520 4.669626 2.000000 2.000000
## AT2G20520 4.362852 2.000000 2.000000
## AT5G42900 6.975885 5.696053 5.877483
## AT1G54970 4.292813 4.431266 2.000000
## AT5G22270 5.521243 4.431266 6.387045
## AT2G20560 5.359345 4.220759 6.827548
## AT1G28480 6.472931 4.364452 3.166852
## AT3G53800 5.012379 5.553369 5.609626
## AT5G61660 5.943137 5.057064 4.902094
## AT5G18270 5.824040 5.850508 5.667324
## AT3G10040 5.176956 4.969858 6.652895
## AT4G03440 5.798994 6.033672 5.387309
## AT3G04070 5.773505 4.364452 6.082253
## AT3G10710 5.426300 3.676643 4.387837
## AT1G79320 4.219199 5.326454 5.486810
## AT1G64480 3.675278 3.782796 5.802215
## AT3G05930 5.012379 4.614932 5.609626
## AT1G01660 5.176956 4.924194 5.722803
## AT5G25190 3.300147 3.974202 5.124381
## AT4G35180 2.000000 4.828289 3.318609
## AT1G16440 3.560741 4.431266 4.083231
## AT2G46860 2.314704 4.061155 3.166852
## AT1G25240 3.149768 3.437572 2.320823
## AT1G79860 3.972721 2.982853 2.320823
## Ws_FLT_Alight_Rep3 Col0PhyD_FLT_Alight_Rep1 Col0PhyD_FLT_Alight_Rep2
## AT3G62040 7.031744 6.163084 6.702935
## AT5G05960 7.053267 8.740140 6.881790
## AT5G13930 2.000000 2.000000 2.000000
## AT2G21640 4.933077 4.833612 4.563350
## AT4G31910 6.809475 7.448069 7.008249
## AT3G03780 7.270970 7.439945 7.349696
## AT2G40900 7.435714 7.579610 7.417571
## AT2G41480 6.205850 5.104240 5.833813
## AT5G63850 7.351355 8.338362 6.986065
## AT3G54500 6.634907 5.927733 7.030096
## AT3G02850 6.224941 7.398623 8.007849
## AT5G37260 6.531356 6.527499 5.929912
## AT4G31730 6.834551 6.258561 6.401509
## AT3G23810 5.860028 5.588735 5.975663
## AT3G17609 4.885877 4.676525 4.438215
## AT3G26830 2.000000 4.369446 3.155553
## AT5G05270 4.734235 5.400615 4.149763
## AT2G46830 3.307413 4.147957 4.502139
## AT3G51240 2.987914 2.985916 3.887889
## AT3G09600 4.734235 4.299328 5.368837
## AT5G17300 5.226228 5.296478 4.732791
## AT5G47990 2.576916 2.000000 2.576356
## AT4G01440 3.568825 5.856274 3.155553
## AT4G09950 5.107804 5.646359 4.227460
## AT1G78580 2.797002 5.433722 4.884407
## AT5G50120 2.987914 4.500219 2.576356
## AT3G54820 4.503539 3.886187 2.796280
## AT5G44350 4.623494 3.978823 3.306400
## AT2G47560 3.156490 2.575589 2.576356
## AT3G57020 3.981833 2.575589 2.987071
## AT3G06020 2.000000 2.316311 2.000000
## AT5G08640 2.000000 2.316311 2.000000
## AT3G03770 4.228798 4.369446 3.980563
## AT2G25680 2.987914 3.305011 2.796280
## AT1G30380 4.151081 3.566154 3.442957
## AT3G56730 3.568825 3.154268 4.732791
## AT5G56720 3.981833 5.332032 2.987071
## AT5G64940 4.439602 4.436314 3.980563
## AT2G47460 3.307413 3.566154 2.576356
## AT2G02020 3.156490 2.985916 3.442957
## AT5G50800 3.156490 2.000000 2.316770
## AT4G24670 2.797002 3.441483 3.442957
## AT1G29910 3.568825 2.316311 2.576356
## AT1G11700 3.683678 3.978823 3.682507
## AT4G25830 2.576916 2.316311 2.987071
## AT4G15430 2.317106 3.566154 2.987071
## AT4G26790 3.790058 3.305011 4.067642
## AT1G68585 3.683678 2.985916 2.316770
## AT5G13630 2.317106 2.316311 2.796280
## AT1G62710 3.307413 3.441483 2.796280
## AT3G05880 12.888441 12.673667 13.054522
## AT3G44300 11.557900 11.561850 11.952405
## AT2G26400 10.168102 10.457603 9.926873
## AT3G54040 10.376678 9.790403 10.894433
## AT1G19960 10.373473 10.728316 10.674528
## AT5G23220 10.065928 9.905501 9.557245
## AT5G24530 8.918439 9.679190 10.408730
## AT5G22555 9.912464 9.178902 7.781848
## AT3G56400 8.530575 9.254966 9.284803
## AT5G05500 9.597902 7.885058 7.963123
## AT5G66170 8.897769 8.360052 9.742330
## AT1G56300 7.523144 8.848454 9.219751
## AT1G51420 8.195223 9.016304 9.233940
## AT5G01210 7.185841 9.479646 9.318483
## AT3G21510 8.998282 7.943693 8.077695
## AT5G66780 5.300100 4.882391 5.499865
## AT3G22121 8.590686 7.879061 8.869064
## AT5G07010 7.289225 8.275836 8.960074
## AT5G41280 9.221440 8.229455 7.505974
## AT5G13330 8.219223 8.385657 8.482108
## AT1G49720 8.252166 8.439622 9.013144
## AT3G22120 8.619827 7.760114 8.536545
## AT2G46680 6.998847 8.215245 8.174054
## AT5G15120 7.243148 8.252832 7.417571
## AT3G53160 6.419795 7.448069 7.794668
## AT2G18690 6.452559 6.805586 7.498157
## AT2G15960 6.998847 5.927733 7.940229
## AT3G17790 7.777065 7.511467 7.632756
## AT4G13195 6.334472 7.623314 7.768914
## AT5G02810 7.402560 7.848697 8.441927
## AT4G13390 5.784828 5.466086 7.574479
## AT2G44080 7.648631 7.439945 7.762402
## AT1G12040 6.531356 5.400615 6.756338
## AT1G22770 7.156310 8.038210 7.788273
## AT4G33070 7.270970 7.836371 7.409260
## AT3G52770 6.021603 4.833612 5.648505
## AT4G33980 7.053267 7.142413 7.366967
## AT2G43570 4.623494 6.512082 6.544984
## AT2G36470 5.908068 7.112056 7.857113
## AT1G06460 4.885877 6.542753 7.425836
## AT1G48930 6.871366 5.806588 5.906481
## AT5G48175 6.186502 7.049356 7.278470
## AT5G02230 5.226228 4.783127 5.402726
## AT1G11210 5.263637 6.572785 7.314523
## AT4G12290 6.452559 6.415951 7.030096
## AT5G18470 5.335664 4.369446 6.589805
## AT3G23150 6.186502 6.727640 6.702935
## AT5G57540 4.734235 3.566154 5.619977
## AT5G24470 6.846927 6.915138 6.529729
## AT5G61650 5.884248 5.296478 7.072823
## AT1G02450 5.437381 5.701770 5.648505
## AT5G19790 5.678047 3.886187 6.084069
## AT2G28690 5.784828 6.645240 4.931600
## AT2G05520 2.317106 6.330640 6.450937
## AT2G20520 2.000000 2.000000 5.676480
## AT5G42900 6.546612 5.400615 5.435838
## AT1G54970 4.503539 3.305011 5.676480
## AT5G22270 5.592433 5.433722 6.845286
## AT2G20560 5.066066 5.184234 5.975663
## AT1G28480 3.981833 2.575589 4.678492
## AT3G53800 6.419795 5.950788 6.104806
## AT5G61660 5.370373 4.882391 6.647478
## AT5G18270 5.621539 5.466086 5.676480
## AT3G10040 5.592433 6.039489 6.063029
## AT4G03440 6.262383 5.995820 5.298572
## AT3G04070 4.623494 4.369446 5.703923
## AT3G10710 3.307413 3.886187 4.149763
## AT1G79320 3.790058 3.680902 3.442957
## AT1G64480 5.226228 4.225627 5.368837
## AT3G05930 4.933077 5.260025 4.371327
## AT1G01660 4.068937 4.147957 3.567698
## AT5G25190 4.734235 5.019549 4.622069
## AT4G35180 4.734235 3.154268 3.980563
## AT1G16440 2.987914 3.154268 3.682507
## AT2G46860 3.981833 2.575589 2.000000
## AT1G25240 2.000000 2.000000 4.502139
## AT1G79860 3.790058 2.316311 2.576356
## Col0PhyD_FLT_Alight_Rep3
## AT3G62040 6.510881
## AT5G05960 6.699485
## AT5G13930 2.000000
## AT2G21640 3.977886
## AT4G31910 8.160672
## AT3G03780 6.878324
## AT2G40900 6.346916
## AT2G41480 6.398092
## AT5G63850 7.293113
## AT3G54500 6.080693
## AT3G02850 5.830478
## AT5G37260 6.142022
## AT4G31730 5.221506
## AT3G23810 6.431227
## AT3G17609 3.565322
## AT3G26830 4.224640
## AT5G05270 4.832533
## AT2G46830 2.575176
## AT3G51240 2.985295
## AT3G09600 4.619065
## AT5G17300 4.974167
## AT5G47990 2.000000
## AT4G01440 4.298327
## AT4G09950 6.541551
## AT1G78580 4.619065
## AT5G50120 4.146985
## AT3G54820 2.000000
## AT5G44350 4.146985
## AT2G47560 2.316064
## AT3G57020 2.575176
## AT3G06020 2.000000
## AT5G08640 2.000000
## AT3G03770 4.560370
## AT2G25680 2.794760
## AT1G30380 4.064912
## AT3G56730 3.153577
## AT5G56720 4.435290
## AT5G64940 2.316064
## AT2G47460 2.316064
## AT2G02020 2.575176
## AT5G50800 2.000000
## AT4G24670 4.499185
## AT1G29910 3.153577
## AT1G11700 2.575176
## AT4G25830 2.316064
## AT4G15430 3.153577
## AT4G26790 3.977886
## AT1G68585 2.575176
## AT5G13630 2.794760
## AT1G62710 2.794760
## AT3G05880 12.809855
## AT3G44300 12.211254
## AT2G26400 9.020512
## AT3G54040 9.887934
## AT1G19960 10.129153
## AT5G23220 9.779536
## AT5G24530 9.946405
## AT5G22555 9.143073
## AT3G56400 9.438213
## AT5G05500 8.660726
## AT5G66170 9.750294
## AT1G56300 9.039439
## AT1G51420 8.947955
## AT5G01210 7.636363
## AT3G21510 9.127994
## AT5G66780 4.729744
## AT3G22121 8.228217
## AT5G07010 8.237613
## AT5G41280 7.998802
## AT5G13330 9.031358
## AT1G49720 8.705428
## AT3G22120 8.063633
## AT2G46680 7.058779
## AT5G15120 8.185160
## AT3G53160 7.930920
## AT2G18690 7.692104
## AT2G15960 8.712184
## AT3G17790 7.284072
## AT4G13195 7.470944
## AT5G02810 8.068906
## AT4G13390 5.464944
## AT2G44080 7.161081
## AT1G12040 7.346197
## AT1G22770 7.877827
## AT4G33070 6.495298
## AT3G52770 5.527567
## AT4G33980 7.841313
## AT2G43570 6.161898
## AT2G36470 7.865758
## AT1G06460 7.901665
## AT1G48930 6.541551
## AT5G48175 6.925598
## AT5G02230 5.994643
## AT1G11210 7.363467
## AT4G12290 6.960063
## AT5G18470 7.685253
## AT3G23150 7.110837
## AT5G57540 2.000000
## AT5G24470 5.496595
## AT5G61650 4.298327
## AT1G02450 4.499185
## AT5G19790 5.018448
## AT2G28690 6.526298
## AT2G05520 6.080693
## AT2G20520 2.000000
## AT5G42900 5.805423
## AT1G54970 2.794760
## AT5G22270 5.399479
## AT2G20560 6.902155
## AT1G28480 3.304264
## AT3G53800 6.238776
## AT5G61660 3.786301
## AT5G18270 4.928483
## AT3G10040 5.221506
## AT4G03440 6.059657
## AT3G04070 5.830478
## AT3G10710 4.560370
## AT1G79320 4.064912
## AT1G64480 5.143678
## AT3G05930 5.903133
## AT1G01660 3.786301
## AT5G25190 5.753969
## AT4G35180 4.224640
## AT1G16440 3.565322
## AT2G46860 2.575176
## AT1G25240 2.316064
## AT1G79860 2.985295
##
## $bar
## AT3G62040 AT5G05960 AT5G13930 AT2G21640 AT4G31910 AT3G03780 AT2G40900 AT2G41480
## -1 -1 -1 -1 -1 -1 -1 -1
## AT5G63850 AT3G54500 AT3G02850 AT5G37260 AT4G31730 AT3G23810 AT3G17609 AT3G26830
## -1 -1 -1 -1 -1 -1 -1 -1
## AT5G05270 AT2G46830 AT3G51240 AT3G09600 AT5G17300 AT5G47990 AT4G01440 AT4G09950
## -1 -1 -1 -1 -1 -1 -1 -1
## AT1G78580 AT5G50120 AT3G54820 AT5G44350 AT2G47560 AT3G57020 AT3G06020 AT5G08640
## -1 -1 -1 -1 -1 -1 -1 -1
## AT3G03770 AT2G25680 AT1G30380 AT3G56730 AT5G56720 AT5G64940 AT2G47460 AT2G02020
## -1 -1 -1 -1 -1 -1 -1 -1
## AT5G50800 AT4G24670 AT1G29910 AT1G11700 AT4G25830 AT4G15430 AT4G26790 AT1G68585
## -1 -1 -1 -1 -1 -1 -1 -1
## AT5G13630 AT1G62710 AT3G05880 AT3G44300 AT2G26400 AT3G54040 AT1G19960 AT5G23220
## -1 -1 1 1 1 1 1 1
## AT5G24530 AT5G22555 AT3G56400 AT5G05500 AT5G66170 AT1G56300 AT1G51420 AT5G01210
## 1 1 1 1 1 1 1 1
## AT3G21510 AT5G66780 AT3G22121 AT5G07010 AT5G41280 AT5G13330 AT1G49720 AT3G22120
## 1 1 1 1 1 1 1 1
## AT2G46680 AT5G15120 AT3G53160 AT2G18690 AT2G15960 AT3G17790 AT4G13195 AT5G02810
## 1 1 1 1 1 1 1 1
## AT4G13390 AT2G44080 AT1G12040 AT1G22770 AT4G33070 AT3G52770 AT4G33980 AT2G43570
## 1 1 1 1 1 1 1 1
## AT2G36470 AT1G06460 AT1G48930 AT5G48175 AT5G02230 AT1G11210 AT4G12290 AT5G18470
## 1 1 1 1 1 1 1 1
## AT3G23150 AT5G57540 AT5G24470 AT5G61650 AT1G02450 AT5G19790 AT2G28690 AT2G05520
## 1 1 1 1 1 1 1 1
## AT2G20520 AT5G42900 AT1G54970 AT5G22270 AT2G20560 AT1G28480 AT3G53800 AT5G61660
## 1 1 1 1 1 1 1 1
## AT5G18270 AT3G10040 AT4G03440 AT3G04070 AT3G10710 AT1G79320 AT1G64480 AT3G05930
## 1 1 1 1 1 1 1 1
## AT1G01660 AT5G25190 AT4G35180 AT1G16440 AT2G46860 AT1G25240 AT1G79860
## 1 1 1 1 1 1 1
# Save gene lists and data into files
write.csv( selectedHeatmap.data()$genes, 'heatmap.data.csv')
write.csv(DEG.data(),'DEG.data.csv' )
write(AllGeneListsGMT() ,'AllGeneListsGMT.gmt')
input_selectGO2 <- 'GOBP' #Gene set category
geneListData.out <- geneListData()
volcanoPlot()
scatterPlot()
MAplot()
geneListGOTable.out <- geneListGOTable()
# Read pathway data again
GeneSets.out <-readGeneSets( geneSetFile,
convertedData.out, input_selectGO2,input_selectOrg,
c(input_minSetSize, input_maxSetSize) )
input_removeRedudantSets <- TRUE #Remove highly redundant gene sets?
results <- geneListGO() #Enrichment analysis
results$adj.Pval <- format( results$adj.Pval,digits=3 )
kable( results, row.names=FALSE) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%")
| Direction | adj.Pval | nGenes | Pathways |
|---|---|---|---|
| Down regulated | 3.2e-06 | 6 | Flavonoid metabolic process |
| 1.4e-05 | 16 | Response to abiotic stimulus | |
| 1.4e-05 | 5 | Flavonoid biosynthetic process | |
| 1.6e-05 | 6 | Circadian rhythm | |
| 1.6e-05 | 8 | Response to auxin | |
| 1.9e-05 | 6 | Rhythmic process | |
| 1.5e-04 | 9 | Response to light stimulus | |
| 1.8e-04 | 9 | Response to radiation | |
| 5.3e-04 | 3 | Neutral amino acid transport | |
| 5.8e-04 | 4 | Response to UV-B | |
| Up regulated | 2.0e-06 | 9 | Phosphorelay signal transduction system |
| 5.4e-06 | 20 | Response to organic substance | |
| 7.0e-06 | 18 | Response to endogenous stimulus | |
| 7.0e-06 | 18 | Response to hormone | |
| 1.7e-05 | 17 | Response to oxygen-containing compound | |
| 2.0e-05 | 9 | Response to organic cyclic compound | |
| 8.9e-05 | 8 | Response to antibiotic | |
| 1.4e-04 | 16 | System development | |
| 1.6e-04 | 10 | Intracellular signal transduction | |
| 1.6e-04 | 15 | Cellular response to chemical stimulus |
STRING-db API access. We need to find the taxonomy id of your species, this used by STRING. First we try to guess the ID based on iDEP’s database. Users can also skip this step and assign NCBI taxonomy id directly by findTaxonomyID.out = 10090 # mouse 10090, human 9606 etc.
STRING10_species = read.csv(STRING10_speciesFile)
ix = grep('Arabidopsis thaliana', STRING10_species$official_name )
findTaxonomyID.out <- STRING10_species[ix,1] # find taxonomyID
findTaxonomyID.out
## [1] 3702
Enrichment analysis using STRING
STRINGdb_geneList.out <- STRINGdb_geneList() #convert gene lists
## Warning: we couldn't map to STRING 0% of your identifiers
input_STRINGdbGO <- 'Process' #'Process', 'Component', 'Function', 'KEGG', 'Pfam', 'InterPro'
results <- stringDB_GO_enrichmentData() # enrichment using STRING
## Warning in string_db$get_enrichment(ids, category = input_STRINGdbGO, methodMT =
## "fdr", : methodMT parameter is depecated. Only FDR correction is available.
## Warning in string_db$get_enrichment(ids, category = input_STRINGdbGO, methodMT =
## "fdr", : iea parameter is deprecated.
## [1] "Process"
## Warning in string_db$get_enrichment(ids, category = input_STRINGdbGO, methodMT =
## "fdr", : methodMT parameter is depecated. Only FDR correction is available.
## Warning in string_db$get_enrichment(ids, category = input_STRINGdbGO, methodMT =
## "fdr", : iea parameter is deprecated.
## [1] "Process"
results$adj.Pval <- format( results$adj.Pval,digits=3 )
kable( results, row.names=FALSE) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%")
| “No significant enrichment found.” | adj.Pval |
|---|---|
| No significant enrichment found. | NULL |
PPI network retrieval and analysis
input_nGenesPPI <- 100 #Number of top genes for PPI retrieval and analysis
stringDB_network1(1) #Show PPI network
Generating interactive PPI
write(stringDB_network_link(), 'PPI_results.html') # write results to html file
## Warning: 'string_db$get_link' is deprecated.
## Use 'Contact developers to request functionality' instead.
## See help("Deprecated")
## Warning: we couldn't map to STRING 0% of your identifiers
## Warning: 'string_db$get_link' is deprecated.
## Use 'Contact developers to request functionality' instead.
## See help("Deprecated")
## Warning: 'string_db$get_link' is deprecated.
## Use 'Contact developers to request functionality' instead.
## See help("Deprecated")
browseURL('PPI_results.html') # open in browser
input_selectContrast1 <- 'Microgravity-Terrestrial' #select Comparison
#input_selectContrast1 = limma.out$comparisons[3] # manually set
input_selectGO <- 'GOBP' #Gene set category
#input_selectGO='custom' # if custom gmt file
input_minSetSize <- 15 #Min size for gene set
input_maxSetSize <- 2000 #Max size for gene set
# Read pathway data again
GeneSets.out <-readGeneSets( geneSetFile,
convertedData.out, input_selectGO,input_selectOrg,
c(input_minSetSize, input_maxSetSize) )
input_pathwayPvalCutoff <- 0.2 #FDR cutoff
input_nPathwayShow <- 30 #Top pathways to show
input_absoluteFold <- FALSE #Use absolute values of fold-change?
input_GenePvalCutoff <- 1 #FDR to remove genes
input_pathwayMethod = 1 # 1 GAGE
gagePathwayData.out <- gagePathwayData() # pathway analysis using GAGE
results <- gagePathwayData.out #Enrichment analysis for k-Means clusters
results$adj.Pval <- format( results$adj.Pval,digits=3 )
kable( results, row.names=FALSE) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%")
| Direction | GAGE analysis: Microgravity vs Terrestrial | statistic | Genes | adj.Pval |
|---|---|---|---|---|
| Down | Photosynthesis | -5.401 | 223 | 1.1e-04 |
| Ribonucleoprotein complex biogenesis | -5.01 | 438 | 3.5e-04 | |
| RNA modification | -4.8591 | 321 | 4.9e-04 | |
| Ribosome biogenesis | -4.734 | 343 | 7.0e-04 | |
| NcRNA metabolic process | -4.2086 | 425 | 5.6e-03 | |
| NcRNA processing | -4.1143 | 357 | 7.2e-03 | |
| Cellular response to DNA damage stimulus | -3.7807 | 337 | 2.3e-02 | |
| RRNA processing | -3.7162 | 239 | 2.5e-02 | |
| DNA repair | -3.7091 | 314 | 2.5e-02 | |
| RRNA metabolic process | -3.6563 | 244 | 2.8e-02 | |
| Up | Cellular response to decreased oxygen levels | 7.4246 | 176 | 3.4e-10 |
| Cellular response to oxygen levels | 7.4246 | 176 | 3.4e-10 | |
| Cellular response to hypoxia | 7.3912 | 175 | 3.4e-10 | |
| Response to hypoxia | 7.0149 | 197 | 1.8e-09 | |
| Response to oxygen levels | 6.991 | 201 | 1.8e-09 | |
| Response to decreased oxygen levels | 6.9904 | 200 | 1.8e-09 | |
| Root epidermal cell differentiation | 4.1893 | 115 | 5.4e-03 | |
| Plant epidermal cell differentiation | 4.0288 | 132 | 7.7e-03 | |
| Response to toxic substance | 4.0187 | 275 | 7.7e-03 | |
| Trichoblast differentiation | 3.938 | 102 | 1.1e-02 | |
| Cell maturation | 3.6762 | 96 | 2.2e-02 | |
| Trichoblast maturation | 3.6762 | 96 | 2.2e-02 | |
| Root hair cell differentiation | 3.6762 | 96 | 2.2e-02 | |
| Anatomical structure maturation | 3.5015 | 151 | 3.2e-02 | |
| Response to antibiotic | 3.4886 | 255 | 3.2e-02 | |
| Antibiotic metabolic process | 3.4875 | 188 | 3.2e-02 | |
| Antibiotic catabolic process | 3.455 | 78 | 3.8e-02 | |
| Response to drug | 3.4042 | 482 | 3.8e-02 | |
| Cellular response to toxic substance | 3.3863 | 148 | 3.8e-02 | |
| Response to reactive oxygen species | 3.3836 | 145 | 3.8e-02 |
pathwayListData.out = pathwayListData()
enrichmentPlot(pathwayListData.out, 25 )
enrichmentNetwork(pathwayListData.out )
enrichmentNetworkPlotly(pathwayListData.out)
## Warning: `arrange_()` is deprecated as of dplyr 0.7.0.
## Please use `arrange()` instead.
## See vignette('programming') for more help
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.
input_pathwayMethod = 3 # 1 fgsea
fgseaPathwayData.out <- fgseaPathwayData() #Pathway analysis using fgsea
## Warning in fgsea(pathways = gmt, stats = fold, minSize = input_minSetSize, :
## You are trying to run fgseaSimple. It is recommended to use fgseaMultilevel. To
## run fgseaMultilevel, you need to remove the nperm argument in the fgsea function
## call.
results <- fgseaPathwayData.out #Enrichment analysis for k-Means clusters
results$adj.Pval <- format( results$adj.Pval,digits=3 )
kable( results, row.names=FALSE) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%")
| Direction | GSEA analysis: Microgravity vs Terrestrial | NES | Genes | adj.Pval |
|---|---|---|---|---|
| Down | Photosynthesis | -2.3258 | 223 | 6.5e-03 |
| Flavonoid metabolic process | -2.3107 | 68 | 6.5e-03 | |
| Response to UV-B | -2.2799 | 59 | 6.5e-03 | |
| Flavonoid biosynthetic process | -2.2798 | 50 | 6.5e-03 | |
| Response to UV | -2.1905 | 95 | 6.5e-03 | |
| Regulation of flavonoid biosynthetic process | -2.1518 | 16 | 6.5e-03 | |
| Regulation of anthocyanin metabolic process | -2.0566 | 19 | 6.5e-03 | |
| Response to gravity | -2.0493 | 78 | 1.0e-02 | |
| Photosynthesis, light reaction | -2.011 | 119 | 6.5e-03 | |
| Anthocyanin-containing compound biosynthetic process | -1.9906 | 20 | 1.4e-02 | |
| Anthocyanin-containing compound metabolic process | -1.9898 | 35 | 1.4e-02 | |
| Regulation of response to red or far red light | -1.9835 | 34 | 1.6e-02 | |
| Response to far red light | -1.9802 | 45 | 1.0e-02 | |
| Response to red light | -1.9735 | 55 | 1.6e-02 | |
| Up | Cellular response to decreased oxygen levels | 2.4397 | 176 | 6.5e-03 |
| Cellular response to oxygen levels | 2.4397 | 176 | 6.5e-03 | |
| Cellular response to hypoxia | 2.4371 | 175 | 6.5e-03 | |
| Response to hypoxia | 2.3544 | 197 | 6.5e-03 | |
| Response to decreased oxygen levels | 2.3491 | 200 | 6.5e-03 | |
| Response to oxygen levels | 2.3466 | 201 | 6.5e-03 | |
| Root epidermal cell differentiation | 2.2177 | 115 | 6.5e-03 | |
| Trichoblast differentiation | 2.2171 | 102 | 6.5e-03 | |
| Plant epidermal cell differentiation | 2.1658 | 132 | 6.5e-03 | |
| Cell maturation | 2.1644 | 96 | 6.5e-03 | |
| Trichoblast maturation | 2.1644 | 96 | 6.5e-03 | |
| Root hair cell differentiation | 2.1644 | 96 | 6.5e-03 | |
| Root hair cell development | 2.1025 | 78 | 6.5e-03 | |
| Root hair elongation | 2.0496 | 58 | 6.5e-03 | |
| Response to hydrogen peroxide | 2.0103 | 65 | 6.5e-03 | |
| Indole glucosinolate metabolic process | 1.9891 | 27 | 9.8e-03 |
pathwayListData.out = pathwayListData()
enrichmentPlot(pathwayListData.out, 25 )
enrichmentNetwork(pathwayListData.out )
enrichmentNetworkPlotly(pathwayListData.out)
PGSEAplot() # pathway analysis using PGSEA
##
## Computing P values using ANOVA
input_selectContrast2 <- 'Terrestrial-Microgravity' #select Comparison
#input_selectContrast2 = limma.out$comparisons[3] # manually set
input_limmaPvalViz <- 0.1 #FDR to filter genes
input_limmaFCViz <- 2 #FDR to filter genes
genomePlotly() # shows fold-changes on the genome
## Warning in eval(quote(list(...)), env): NAs introduced by coercion
## Warning in genomePlotly(): NAs introduced by coercion
input_nGenesBiclust <- 1000 #Top genes for biclustering
input_biclustMethod <- 'BCCC()' #Method: 'BCCC', 'QUBIC', 'runibic' ...
biclustering.out = biclustering() # run analysis
input_selectBicluster <- 1 #select a cluster
biclustHeatmap() # heatmap for selected cluster
input_selectGO4 <- 'GOBP' #Gene set category
# Read pathway data again
GeneSets.out <-readGeneSets( geneSetFile,
convertedData.out, input_selectGO4,input_selectOrg,
c(input_minSetSize, input_maxSetSize) )
results <- geneListBclustGO() #Enrichment analysis for k-Means clusters
results$adj.Pval <- format( results$adj.Pval,digits=3 )
kable( results, row.names=FALSE) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%")
| adj.Pval | Genes | Pathways |
|---|---|---|
| 1.9e-120 | 192 | Peptide metabolic process |
| 1.9e-117 | 182 | Translation |
| 3.3e-117 | 182 | Peptide biosynthetic process |
| 8.8e-113 | 185 | Amide biosynthetic process |
| 2.1e-111 | 196 | Cellular amide metabolic process |
| 5.5e-96 | 238 | Organonitrogen compound biosynthetic process |
| 1.4e-68 | 151 | Response to inorganic substance |
| 6.0e-57 | 101 | Response to metal ion |
| 1.3e-53 | 86 | Response to cadmium ion |
| 4.4e-49 | 197 | Response to abiotic stimulus |
input_mySoftPower <- 5 #SoftPower to cutoff
input_nGenesNetwork <- 1000 #Number of top genes
input_minModuleSize <- 20 #Module size minimum
wgcna.out = wgcna() # run WGCNA
## Warning: executing %dopar% sequentially: no parallel backend registered
## Power SFT.R.sq slope truncated.R.sq mean.k. median.k. max.k.
## 1 1 0.7780 1.540 0.918 368.00 378.00 520.0
## 2 2 0.2370 0.285 0.681 189.00 190.00 333.0
## 3 3 0.0936 -0.126 0.651 114.00 108.00 234.0
## 4 4 0.5360 -0.387 0.797 74.60 67.20 176.0
## 5 5 0.7270 -0.553 0.905 52.10 44.20 140.0
## 6 6 0.8430 -0.724 0.971 38.10 30.50 116.0
## 7 7 0.8550 -0.824 0.955 28.80 21.40 98.1
## 8 8 0.9000 -0.922 0.984 22.40 15.90 84.7
## 9 9 0.9090 -0.995 0.969 17.80 12.00 74.2
## 10 10 0.9080 -1.060 0.953 14.40 9.25 65.6
## 11 12 0.9290 -1.130 0.950 9.86 5.67 52.5
## 12 14 0.9370 -1.180 0.941 7.06 3.53 43.0
## 13 16 0.9550 -1.210 0.949 5.24 2.34 35.8
## 14 18 0.9530 -1.220 0.940 4.00 1.54 30.2
## 15 20 0.9730 -1.230 0.965 3.12 1.08 25.8
## TOM calculation: adjacency..
## ..will not use multithreading.
## Fraction of slow calculations: 0.000000
## ..connectivity..
## ..matrix multiplication (system BLAS)..
## ..normalization..
## ..done.
softPower() # soft power curve
modulePlot() # plot modules
listWGCNA.Modules.out = listWGCNA.Modules() #modules
input_selectGO5 <- 'GOBP' #Gene set category
# Read pathway data again
GeneSets.out <-readGeneSets( geneSetFile,
convertedData.out, input_selectGO5,input_selectOrg,
c(input_minSetSize, input_maxSetSize) )
input_selectWGCNA.Module <- 'Entire network' #Select a module
input_topGenesNetwork <- 10 #SoftPower to cutoff
input_edgeThreshold <- 0.4 #Number of top genes
moduleNetwork() # show network of top genes in selected module
## softConnectivity: FYI: connecitivty of genes with less than 12 valid samples will be returned as NA.
## ..calculating connectivities..
input_removeRedudantSets <- TRUE #Remove redundant gene sets
results <- networkModuleGO() #Enrichment analysis of selected module
results$adj.Pval <- format( results$adj.Pval,digits=3 )
kable( results, row.names=FALSE) %>%
kable_styling(bootstrap_options = c("striped", "hover")) %>%
scroll_box(width = "100%")
| adj.Pval | Genes | Pathways |
|---|---|---|
| 1.9e-120 | 192 | Peptide metabolic process |
| 1.9e-117 | 182 | Translation |
| 3.3e-117 | 182 | Peptide biosynthetic process |
| 8.8e-113 | 185 | Amide biosynthetic process |
| 2.1e-111 | 196 | Cellular amide metabolic process |
| 5.5e-96 | 238 | Organonitrogen compound biosynthetic process |
| 1.4e-68 | 151 | Response to inorganic substance |
| 6.0e-57 | 101 | Response to metal ion |
| 1.3e-53 | 86 | Response to cadmium ion |
| 4.4e-49 | 197 | Response to abiotic stimulus |